Senior AI Full stack Software Engineer

Success Profile

What makes a successful Senior AI Full stack Software Engineer? Here are the top traits.

• Conceptual
• Proactive
• Problem-Solver
• Strategic
• Tech-Savvy
• Visual Thinker

Culture

Innovate
Foster a digital mindset to drive IT transformation across McKesson through our evolving data and technology tools.
Grow
Join a supportive environment where you can advance your career and develop both personally and professionally.

Benefits

• Coverage you can rely on- Medical, Dental, and Vision
• Health Spending Accounts
• Flexible Spending Accounts
• Benefits that go beyond your base pay- 401(k) (U.S.)
• Pension (Canada)
• Employee Stock Purchase Plan
• Mental Health Programs
• Flexible Schedules
• Paid Time Off
• Wellness Program
• Education Reimbursement
• Volunteer Opportunities
• Flexible Work Environment
• A culture powered by belonging

Responsibilities

• Lead AI-Driven Healthcare Solutions: Design and deploy AI applications that support decision-making, patient engagement, and operational efficiency.
• Integrate AI into EHRs and Clinical Systems: Build scalable systems that incorporate LLMs, voice/image recognition, and document parsing into existing healthcare IT infrastructure.
• Develop and Optimize Data Pipelines: Ensure secure, HIPAA-compliant data pipelines for training and deploying AI models using structured and unstructured healthcare data (e.g., clinical notes, imaging, lab results).
• Model Evaluation and Compliance: Apply rigorous evaluation metrics (e.g., sensitivity, specificity, AUC-ROC) and ensure models meet regulatory and ethical standards.
• Mentor and Lead: Guide junior engineers and contribute to the strategic direction of AI initiatives within the organization.
• Rapid AI prototyping and iteration with product representatives to vet multiple concepts

Qualifications

• 10+ years of software engineering experience, with 4+ years in AI/ML development.
• B.S. degree in Computer Science or related engineering discipline, or equivalent experience

Skills

• 2+ years of experience building AI solutions in healthcare or life sciences.
• Deep understanding of healthcare data standards (e.g., HL7, FHIR) and compliance frameworks (e.g., HIPAA, GDPR).
• Healthcare AI Expertise: Proven ability to build AI models for clinical NLP, medical imaging, patient risk stratification, and care personalization.
• LLM & RAG Systems: Skilled in building retrieval-augmented generation systems using tools like Pydantic, Semantic Kernel, LangChain, LlamaIndex, and vector databases.
• Experience writing skills for Claude, Copilot, Codex etc.
• Prompt Engineering & Optimization: Advanced techniques for prompt tuning, caching, and benchmarking.
• Full Stack Development: Proficiency in Python, Node.js, and modern web frameworks.

Preferred Skills

• Cloud & DevOps: Experience with secure cloud environments (AWS/GCP/Azure), containerization (Docker, Kubernetes), and CI/CD pipelines.
• AI Tooling: Familiarity with OpenAI, Hugging Face, PyDanticAI, TensorFlow, PyTorch, and healthcare-specific AI libraries.
• Communication & Leadership: Ability to communicate complex AI concepts to clinical and executive stakeholders and lead cross-functional teams.
• Experience mentoring and developing juniors in development and AI concepts/best practices.